- Hardcover: 736 pages
- Publisher: McGraw Hill Higher Education; 3rd Revised edition edition (Nov 1994)
- Language English
- ISBN-10: 0070426236
- ISBN-13: 978-0070426238
- Product Dimensions: 23.9 x 16 x 3.8 cm
- Amazon Bestsellers Rank: 4,527,096 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Description
Product Description
This text is designed for the first course in probability and statistics taken by students majoring in engineering and the computing sciences. It offers a presentation of applications and theory. This edition also includes expanded coverage of quality control.
--This text refers to an out of print or unavailable edition of this title.
From the Publisher
New and retained examples and exercises are chosen specifically for students in engineering and computer science. Students can therefore work on problems within a context that is familiar and interesting to them.
The presentation is such that students get some understanding of the logic behind the techniques as well as practice using them. Because students will have some understanding of the logic behind the techniques, students are better able to retain the information and are better prepared to apply the techniques.
Data sets for examples and problems are provided in several electronic formats for use with the most popular statistical packages. Students do not have to waste valuable time entering data and data-entry errors are eliminated.
References to statistical analysis packages have been added. This enables students to see how the techniques are applied by using these popular packages.
SSM and IM provided. --This text refers to an alternate Hardcover edition.
The presentation is such that students get some understanding of the logic behind the techniques as well as practice using them. Because students will have some understanding of the logic behind the techniques, students are better able to retain the information and are better prepared to apply the techniques.
Data sets for examples and problems are provided in several electronic formats for use with the most popular statistical packages. Students do not have to waste valuable time entering data and data-entry errors are eliminated.
References to statistical analysis packages have been added. This enables students to see how the techniques are applied by using these popular packages.
SSM and IM provided. --This text refers to an alternate Hardcover edition.
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13 reviews
8 of 8 people found the following review helpful
a standard statistics book for engineers
19 May 2007
Format:Hardcover
I taught a class at upper undergraduate level (mostly junior students) for a non-majors (mostly engineering students, some economics and political science) at a research university using this book.
It was written in the mid 1980s, and has not seen major updates even though it now comes in 4th edition. One of the assignments I gave was to comment whether you recognize the brand names of the mainframe computers mentioned in the problem. Newer stuff like say the bootstrap or machine learning or anything like that is not mentioned anywhere nearly. True, it has all the major results and techniques, but it was written by statisticians as the first course in statistics for to-be-statisticians, rather than the-only-course-in-statistics-you'll-ever-see for engineers. Thus a lot of things could have been presented in a different way with a different depth of exposure. Say the reliability, arguably a more important topic for engineers than moment generating function techniques, deserves a whole separate chapter, rather than being stuck in a middle of the chapter on continuous distributions. Simulations could have been highlighted throughout the book -- a good fraction of my students would probably be geekier than me with computers. I would unite all the confidence intervals under the umbrella of a single chapter, rather than presenting the CI for mean in one chapter and CI for variance in the next one. And so on. There even were errors in the answers in the end of the book, although you would probably expect the fourth edition not to have any.
Students complained a lot about the book in my class, too. Some said it did not help much, although there were others who did not come much to class (admittedly, I am a pretty boring lecturer) and got B's and A's, so apparently it was of some use to them. The price is of course also an issue: I personally won't pay $120 for book of this quality to sit in my professional library, and it sucks that I have my students buy it.
[Wasserman's [ASIN:0387402721 All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)]] is a much more modern book, although in all likelihood it would be difficult for my clientelle. My other favorite is Utts' Seeing Through Statistics (with CD-ROM and InfoTrac ), but this one is on the other side of technicality, being too easy. Finally, for engineering students specifically, Ryan's Modern Engineering Statistics (Hardcover) appears to be a much better text, although I have not taught from it, and my recommendation is based on just browsing through the pages and supplementing the current book with examples and problems from Ryan's book.
It was written in the mid 1980s, and has not seen major updates even though it now comes in 4th edition. One of the assignments I gave was to comment whether you recognize the brand names of the mainframe computers mentioned in the problem. Newer stuff like say the bootstrap or machine learning or anything like that is not mentioned anywhere nearly. True, it has all the major results and techniques, but it was written by statisticians as the first course in statistics for to-be-statisticians, rather than the-only-course-in-statistics-you'll-ever-see for engineers. Thus a lot of things could have been presented in a different way with a different depth of exposure. Say the reliability, arguably a more important topic for engineers than moment generating function techniques, deserves a whole separate chapter, rather than being stuck in a middle of the chapter on continuous distributions. Simulations could have been highlighted throughout the book -- a good fraction of my students would probably be geekier than me with computers. I would unite all the confidence intervals under the umbrella of a single chapter, rather than presenting the CI for mean in one chapter and CI for variance in the next one. And so on. There even were errors in the answers in the end of the book, although you would probably expect the fourth edition not to have any.
Students complained a lot about the book in my class, too. Some said it did not help much, although there were others who did not come much to class (admittedly, I am a pretty boring lecturer) and got B's and A's, so apparently it was of some use to them. The price is of course also an issue: I personally won't pay $120 for book of this quality to sit in my professional library, and it sucks that I have my students buy it.
[Wasserman's [ASIN:0387402721 All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)]] is a much more modern book, although in all likelihood it would be difficult for my clientelle. My other favorite is Utts' Seeing Through Statistics (with CD-ROM and InfoTrac ), but this one is on the other side of technicality, being too easy. Finally, for engineering students specifically, Ryan's Modern Engineering Statistics (Hardcover) appears to be a much better text, although I have not taught from it, and my recommendation is based on just browsing through the pages and supplementing the current book with examples and problems from Ryan's book.
1 of 1 people found the following review helpful
Very Good as Textbook
15 July 2005
Format:Hardcover
This book was recently used as a textbook for an engineering statistics class. Many of the students liked the book and found it easy to read. The level of mathematics in the book is excellent for a college level statistics textbook. I would have given it a five star rating if propogation of error and nonlinear regression analysis were covered in the textbook.
4 of 6 people found the following review helpful
More garbage by professional academics
14 Oct 2004
Format:Hardcover
This book is used in introductory probability and statistics courses, yet it reads like the authors' awkwardly written cliff notes.
The authors insist on using multiple levels of mathematical indirection to introduce even the most basic of theorems. Examples in the reading consist mostly of long drawn out, and totally unreferenceable word problems. There are no diagrams to help visualize concepts until chapter four. Summaries are wordy. Summaries of similar topics are inconsistently worded leading to a lack of parallelism, and gratuitously increasing the difficulty of comparing them.
Overall, this is a useless book to learn or study from.
The authors insist on using multiple levels of mathematical indirection to introduce even the most basic of theorems. Examples in the reading consist mostly of long drawn out, and totally unreferenceable word problems. There are no diagrams to help visualize concepts until chapter four. Summaries are wordy. Summaries of similar topics are inconsistently worded leading to a lack of parallelism, and gratuitously increasing the difficulty of comparing them.
Overall, this is a useless book to learn or study from.
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